Abstract
Scale invariant feature transform (SIFT) is a better corner extraction algorithm, but there are still mismatching problems in the feature matching step. a new matching principle based on vector similarity is proposed and then it is compared with traditional matching principle. Firstly, the matching feature points are detected by the new principle. Mismatching points are further removed by using the mutual mapping theory. Secondly, transformation matrix is calculated by random sample consensus (RANSAC). Furthermore, the matrix is optimized by Levenberg-Marquardt algorithm (L-M). Lastly, image mosaic is realized by image fusion. Experimental results indicate that compared with traditional matching principle, new matching principle has improved matching accuracy. It is able to apply new principle to image registration and image mosaic.
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